| Exception Type | Service | Model | Question Name | Count |
|---|---|---|---|---|
| TimeoutError | openai | gpt-5 | question | 1 |
Note: Each unique exception is counted only once. You may encounter repeated exceptions where retries were attempted.
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:34.946681 |
| Interview ID | 2252 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.045312 |
| Interview ID | 2268 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.050389 |
| Interview ID | 2269 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.101798 |
| Interview ID | 2278 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.349631 |
| Interview ID | 2283 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.354664 |
| Interview ID | 2284 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.366324 |
| Interview ID | 2286 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.372173 |
| Interview ID | 2287 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.377611 |
| Interview ID | 2288 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.382684 |
| Interview ID | 2289 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.388312 |
| Interview ID | 2290 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.393765 |
| Interview ID | 2291 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.399888 |
| Interview ID | 2292 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.406575 |
| Interview ID | 2293 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.416253 |
| Interview ID | 2294 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.424962 |
| Interview ID | 2295 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.432406 |
| Interview ID | 2296 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.439878 |
| Interview ID | 2297 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.446868 |
| Interview ID | 2298 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.453592 |
| Interview ID | 2299 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.459959 |
| Interview ID | 2300 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.465819 |
| Interview ID | 2301 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.471319 |
| Interview ID | 2302 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.476724 |
| Interview ID | 2303 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.482392 |
| Interview ID | 2304 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.488183 |
| Interview ID | 2305 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.494522 |
| Interview ID | 2306 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.499887 |
| Interview ID | 2307 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.505518 |
| Interview ID | 2308 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.511220 |
| Interview ID | 2309 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 5.0 - Agreeableness: 4.75 - Conscientiousness: 4.5 - Neuroticism: 1.0 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """65caa7c0f1403c9b8141857c""", traits = {'prolific_pid': '65caa7c0f1403c9b8141857c', 'age': 40, 'gender': 'female', 'state': 'North Carolina', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'married', 'children': '1 child', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$100,000-$149,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, mainstream', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'important', 'extraversion_score': 5.0, 'agreeableness_score': 4.75, 'conscientiousness_score': 4.5, 'neuroticism_score': 1.0, 'openness_score': 4.5, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 40 years old, identifying as female, living in North Carolina, U.S.. Your ethnicity is black or African American, and you are married, with 1 child. You are working full-time and have attained bachelor’s degree. Your household income is $100,000-$149,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, mainstream brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 5.0
- Agreeableness: 4.75
- Conscientiousness: 4.5
- Neuroticism: 1.0
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.476283 |
| Interview ID | 2340 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.481431 |
| Interview ID | 2341 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.487145 |
| Interview ID | 2342 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.492470 |
| Interview ID | 2343 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.497404 |
| Interview ID | 2344 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.503495 |
| Interview ID | 2345 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.508290 |
| Interview ID | 2346 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.514349 |
| Interview ID | 2347 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.520101 |
| Interview ID | 2348 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.525913 |
| Interview ID | 2349 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.531752 |
| Interview ID | 2350 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.537357 |
| Interview ID | 2351 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.543497 |
| Interview ID | 2352 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.549848 |
| Interview ID | 2353 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.555019 |
| Interview ID | 2354 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.561158 |
| Interview ID | 2355 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.566706 |
| Interview ID | 2356 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.571702 |
| Interview ID | 2357 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.578046 |
| Interview ID | 2358 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.583149 |
| Interview ID | 2359 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.594490 |
| Interview ID | 2361 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.600665 |
| Interview ID | 2362 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.605590 |
| Interview ID | 2363 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.610887 |
| Interview ID | 2364 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.617563 |
| Interview ID | 2365 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.622907 |
| Interview ID | 2366 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.629367 |
| Interview ID | 2367 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.636020 |
| Interview ID | 2368 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:35.641763 |
| Interview ID | 2369 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.867606 |
| Interview ID | 2370 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.873906 |
| Interview ID | 2371 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.879501 |
| Interview ID | 2372 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.887033 |
| Interview ID | 2373 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.892937 |
| Interview ID | 2374 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.901274 |
| Interview ID | 2375 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.907220 |
| Interview ID | 2376 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.912710 |
| Interview ID | 2377 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.919087 |
| Interview ID | 2378 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.925012 |
| Interview ID | 2379 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.931323 |
| Interview ID | 2380 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.937358 |
| Interview ID | 2381 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.942907 |
| Interview ID | 2382 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.948640 |
| Interview ID | 2383 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.953820 |
| Interview ID | 2384 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.959425 |
| Interview ID | 2385 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.965583 |
| Interview ID | 2386 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.971424 |
| Interview ID | 2387 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.976359 |
| Interview ID | 2388 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.981886 |
| Interview ID | 2389 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.988123 |
| Interview ID | 2390 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.993644 |
| Interview ID | 2391 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:52.999430 |
| Interview ID | 2392 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.005192 |
| Interview ID | 2393 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.010268 |
| Interview ID | 2394 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.016074 |
| Interview ID | 2395 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.022563 |
| Interview ID | 2396 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.027550 |
| Interview ID | 2397 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.033194 |
| Interview ID | 2398 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.039399 |
| Interview ID | 2399 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 4.75 - Conscientiousness: 3.5 - Neuroticism: 2.75 - Openness: 4.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """668331f861a6ee98717d3f1c""", traits = {'prolific_pid': '668331f861a6ee98717d3f1c', 'age': 23, 'gender': 'female', 'state': 'Ohio', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Democrat', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'a little', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.25, 'agreeableness_score': 4.75, 'conscientiousness_score': 3.5, 'neuroticism_score': 2.75, 'openness_score': 4.25, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 23 years old, identifying as female, living in Ohio, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. You decline to specify your political ideology, leaving your views undefined. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, sustainable, boutique brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 4.75
- Conscientiousness: 3.5
- Neuroticism: 2.75
- Openness: 4.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.025081 |
| Interview ID | 2430 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.029789 |
| Interview ID | 2431 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.036608 |
| Interview ID | 2432 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.042255 |
| Interview ID | 2433 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.048398 |
| Interview ID | 2434 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.106381 |
| Interview ID | 2435 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.106661 |
| Interview ID | 2436 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.106858 |
| Interview ID | 2437 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.107042 |
| Interview ID | 2438 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.133056 |
| Interview ID | 2439 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.133600 |
| Interview ID | 2440 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.133810 |
| Interview ID | 2441 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.133993 |
| Interview ID | 2442 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.134184 |
| Interview ID | 2443 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.134552 |
| Interview ID | 2444 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.134877 |
| Interview ID | 2445 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.135060 |
| Interview ID | 2446 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.135231 |
| Interview ID | 2447 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.135401 |
| Interview ID | 2448 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.135735 |
| Interview ID | 2449 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.139540 |
| Interview ID | 2450 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.146081 |
| Interview ID | 2451 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.151401 |
| Interview ID | 2452 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.158409 |
| Interview ID | 2453 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.163403 |
| Interview ID | 2454 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.168708 |
| Interview ID | 2455 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.174237 |
| Interview ID | 2456 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.180298 |
| Interview ID | 2457 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.185857 |
| Interview ID | 2458 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.191290 |
| Interview ID | 2459 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.784862 |
| Interview ID | 2460 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.785176 |
| Interview ID | 2461 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.785375 |
| Interview ID | 2462 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.785569 |
| Interview ID | 2463 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.785746 |
| Interview ID | 2464 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.785921 |
| Interview ID | 2465 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.786102 |
| Interview ID | 2466 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:53.786280 |
| Interview ID | 2467 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.073927 |
| Interview ID | 2468 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.074220 |
| Interview ID | 2469 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.074466 |
| Interview ID | 2470 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.074681 |
| Interview ID | 2471 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.074865 |
| Interview ID | 2472 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075055 |
| Interview ID | 2473 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075239 |
| Interview ID | 2474 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075412 |
| Interview ID | 2475 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075621 |
| Interview ID | 2476 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075807 |
| Interview ID | 2477 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.075979 |
| Interview ID | 2478 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.076152 |
| Interview ID | 2479 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.076326 |
| Interview ID | 2480 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.076754 |
| Interview ID | 2481 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.076947 |
| Interview ID | 2482 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.077160 |
| Interview ID | 2483 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.077403 |
| Interview ID | 2484 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.077588 |
| Interview ID | 2485 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.077764 |
| Interview ID | 2486 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.077941 |
| Interview ID | 2487 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.078120 |
| Interview ID | 2488 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.078296 |
| Interview ID | 2489 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 1.0 - Agreeableness: 3.5 - Conscientiousness: 5.0 - Neuroticism: 2.25 - Openness: 4.5 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """63ea4f9fe0e6a3c7a08e3ffc""", traits = {'prolific_pid': '63ea4f9fe0e6a3c7a08e3ffc', 'age': 30, 'gender': 'female', 'state': 'Louisiana', 'country': 'U.S.', 'ethnicity': 'black or African American', 'marital_status': 'living with a partner', 'children': '2 children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'No preference', 'political_ideology': 'Moderately Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': 'more than $500', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 1.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 5.0, 'neuroticism_score': 2.25, 'openness_score': 4.5, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You do not identify with any specific political orientation, indicating no particular preference for major political ideologies.', 'political_ideology_prompt': 'Your political views are moderately liberal, indicating a balanced approach toward progressive ideals.', 'political_strength_prompt': 'Your political strength and orientation are undefined.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 30 years old, identifying as female, living in Louisiana, U.S.. Your ethnicity is black or African American, and you are living with a partner, with 2 children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You do not identify with any specific political orientation, indicating no particular preference for major political ideologies. Your political views are moderately liberal, indicating a balanced approach toward progressive ideals. Your political strength and orientation are undefined. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop weekly and spend more than $500 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 1.0
- Agreeableness: 3.5
- Conscientiousness: 5.0
- Neuroticism: 2.25
- Openness: 4.5
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.973969 |
| Interview ID | 2520 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.974293 |
| Interview ID | 2521 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.974552 |
| Interview ID | 2522 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.974775 |
| Interview ID | 2523 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.975019 |
| Interview ID | 2524 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.975216 |
| Interview ID | 2525 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.975399 |
| Interview ID | 2526 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.975578 |
| Interview ID | 2527 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:36.975773 |
| Interview ID | 2528 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.179523 |
| Interview ID | 2529 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.179823 |
| Interview ID | 2530 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180025 |
| Interview ID | 2531 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180199 |
| Interview ID | 2532 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180377 |
| Interview ID | 2533 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180547 |
| Interview ID | 2534 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180750 |
| Interview ID | 2535 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.180925 |
| Interview ID | 2536 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.181125 |
| Interview ID | 2537 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.181491 |
| Interview ID | 2538 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.181705 |
| Interview ID | 2539 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.181875 |
| Interview ID | 2540 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182032 |
| Interview ID | 2541 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182185 |
| Interview ID | 2542 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182336 |
| Interview ID | 2543 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182487 |
| Interview ID | 2544 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182657 |
| Interview ID | 2545 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182806 |
| Interview ID | 2546 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.182954 |
| Interview ID | 2547 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.183145 |
| Interview ID | 2548 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.183313 |
| Interview ID | 2549 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.876627 |
| Interview ID | 2550 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.877051 |
| Interview ID | 2551 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.877576 |
| Interview ID | 2552 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.877866 |
| Interview ID | 2553 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.878069 |
| Interview ID | 2554 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.878280 |
| Interview ID | 2555 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.878454 |
| Interview ID | 2556 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.878640 |
| Interview ID | 2557 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.878864 |
| Interview ID | 2558 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.879097 |
| Interview ID | 2559 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.879301 |
| Interview ID | 2560 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.879494 |
| Interview ID | 2561 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.879676 |
| Interview ID | 2562 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.879887 |
| Interview ID | 2563 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.880067 |
| Interview ID | 2564 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.880255 |
| Interview ID | 2565 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.880421 |
| Interview ID | 2566 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.880590 |
| Interview ID | 2567 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.880766 |
| Interview ID | 2568 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.881199 |
| Interview ID | 2569 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:54.881521 |
| Interview ID | 2570 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.096912 |
| Interview ID | 2571 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.101441 |
| Interview ID | 2572 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.101701 |
| Interview ID | 2573 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.101878 |
| Interview ID | 2574 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102046 |
| Interview ID | 2575 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102209 |
| Interview ID | 2576 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102388 |
| Interview ID | 2577 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102566 |
| Interview ID | 2578 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102744 |
| Interview ID | 2579 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 2.25 - Conscientiousness: 2.5 - Neuroticism: 1.5 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """5edb487096035b7c2ab90276""", traits = {'prolific_pid': '5edb487096035b7c2ab90276', 'age': 27, 'gender': 'male', 'state': 'Nevada', 'country': 'U.S.', 'ethnicity': 'asian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$75,000-$99,999', 'political_orientation': 'Democrat', 'political_ideology': 'Extremely Liberal', 'shopping_frequency': 'weekly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone, tablet, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 2.25, 'conscientiousness_score': 2.5, 'neuroticism_score': 1.5, 'openness_score': 4.75, 'democrat_strength': 'Strong', 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as a Democrat, reflecting alignment with progressive political ideologies.', 'political_ideology_prompt': 'Your political views are extremely liberal, prioritizing progressive and transformative social policies.', 'political_strength_prompt': "You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 27 years old, identifying as male, living in Nevada, U.S.. Your ethnicity is asian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $75,000-$99,999. You identify as a Democrat, reflecting alignment with progressive political ideologies. Your political views are extremely liberal, prioritizing progressive and transformative social policies. You consider yourself a strong Democrat, firmly aligned with the party's progressive values and policies. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop weekly and spend $50 - $100 per month. You primarily use smartphone, tablet, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 2.25
- Conscientiousness: 2.5
- Neuroticism: 1.5
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.840997 |
| Interview ID | 2610 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.841282 |
| Interview ID | 2611 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.841468 |
| Interview ID | 2612 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.841640 |
| Interview ID | 2613 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.841810 |
| Interview ID | 2614 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842021 |
| Interview ID | 2615 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842188 |
| Interview ID | 2616 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842359 |
| Interview ID | 2617 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842559 |
| Interview ID | 2618 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842724 |
| Interview ID | 2619 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.842884 |
| Interview ID | 2620 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.843044 |
| Interview ID | 2621 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.843216 |
| Interview ID | 2622 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.843379 |
| Interview ID | 2623 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.843822 |
| Interview ID | 2624 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.843998 |
| Interview ID | 2625 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.844170 |
| Interview ID | 2626 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.917878 |
| Interview ID | 2627 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.924952 |
| Interview ID | 2628 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.925224 |
| Interview ID | 2629 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.925491 |
| Interview ID | 2630 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.925665 |
| Interview ID | 2631 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.925832 |
| Interview ID | 2632 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.925990 |
| Interview ID | 2633 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926151 |
| Interview ID | 2634 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926307 |
| Interview ID | 2635 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926463 |
| Interview ID | 2636 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926615 |
| Interview ID | 2637 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926773 |
| Interview ID | 2638 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.926925 |
| Interview ID | 2639 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.102923 |
| Interview ID | 2640 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.103091 |
| Interview ID | 2641 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.103267 |
| Interview ID | 2642 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.103442 |
| Interview ID | 2643 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.103724 |
| Interview ID | 2644 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.104146 |
| Interview ID | 2645 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.104358 |
| Interview ID | 2646 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.104784 |
| Interview ID | 2647 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.104963 |
| Interview ID | 2648 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105120 |
| Interview ID | 2649 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105276 |
| Interview ID | 2650 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105431 |
| Interview ID | 2651 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105586 |
| Interview ID | 2652 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105744 |
| Interview ID | 2653 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.105898 |
| Interview ID | 2654 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106058 |
| Interview ID | 2655 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106208 |
| Interview ID | 2656 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106359 |
| Interview ID | 2657 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106525 |
| Interview ID | 2658 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106694 |
| Interview ID | 2659 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.106855 |
| Interview ID | 2660 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107008 |
| Interview ID | 2661 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107163 |
| Interview ID | 2662 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107327 |
| Interview ID | 2663 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107478 |
| Interview ID | 2664 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107631 |
| Interview ID | 2665 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107783 |
| Interview ID | 2666 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.107938 |
| Interview ID | 2667 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.108095 |
| Interview ID | 2668 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.108250 |
| Interview ID | 2669 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.0 - Agreeableness: 4.25 - Conscientiousness: 1.75 - Neuroticism: 4.75 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """58ab2db50da7f10001de8e34""", traits = {'prolific_pid': '58ab2db50da7f10001de8e34', 'age': 28, 'gender': 'prefer not to say', 'state': 'New York', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working part-time', 'education_level': 'bachelor’s degree', 'household_income': '$50,000-$74,999', 'political_orientation': 'Independent', 'political_ideology': 'Decline to specify', 'shopping_frequency': 'monthly', 'monthly_spend': '$50 - $100', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable', 'social_media_influence': 'not at all', 'eco_friendly_importance': 'important', 'extraversion_score': 2.0, 'agreeableness_score': 4.25, 'conscientiousness_score': 1.75, 'neuroticism_score': 4.75, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Kamala Harris', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You decline to specify your political ideology, leaving your views undefined.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values.', 'social_media_influence_prompt': 'Social media has no influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 28 years old, identifying as prefer not to say, living in New York, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working part-time and have attained bachelor’s degree. Your household income is $50,000-$74,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You decline to specify your political ideology, leaving your views undefined. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Kamala Harris, reflecting alignment with Democratic values. As an online shopper, you shop monthly and spend $50 - $100 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable brands. Social media has no influence on your decision-making process when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.0
- Agreeableness: 4.25
- Conscientiousness: 1.75
- Neuroticism: 4.75
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927092 |
| Interview ID | 2700 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927250 |
| Interview ID | 2701 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927404 |
| Interview ID | 2702 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927564 |
| Interview ID | 2703 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927720 |
| Interview ID | 2704 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.927876 |
| Interview ID | 2705 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.928074 |
| Interview ID | 2706 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.928231 |
| Interview ID | 2707 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.928392 |
| Interview ID | 2708 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.928559 |
| Interview ID | 2709 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.928749 |
| Interview ID | 2710 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929090 |
| Interview ID | 2711 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929248 |
| Interview ID | 2712 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929406 |
| Interview ID | 2713 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929560 |
| Interview ID | 2714 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929717 |
| Interview ID | 2715 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.929878 |
| Interview ID | 2716 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930037 |
| Interview ID | 2717 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930242 |
| Interview ID | 2718 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930406 |
| Interview ID | 2719 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930568 |
| Interview ID | 2720 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930725 |
| Interview ID | 2721 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.930883 |
| Interview ID | 2722 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931038 |
| Interview ID | 2723 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931189 |
| Interview ID | 2724 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931338 |
| Interview ID | 2725 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931497 |
| Interview ID | 2726 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931653 |
| Interview ID | 2727 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931807 |
| Interview ID | 2728 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:37.931961 |
| Interview ID | 2729 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.747406 |
| Interview ID | 2730 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.747703 |
| Interview ID | 2731 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.747884 |
| Interview ID | 2732 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748101 |
| Interview ID | 2733 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748269 |
| Interview ID | 2734 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748432 |
| Interview ID | 2735 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748587 |
| Interview ID | 2736 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748752 |
| Interview ID | 2737 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.748918 |
| Interview ID | 2738 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749072 |
| Interview ID | 2739 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749230 |
| Interview ID | 2740 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749380 |
| Interview ID | 2741 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749536 |
| Interview ID | 2742 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749713 |
| Interview ID | 2743 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.749924 |
| Interview ID | 2744 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.750124 |
| Interview ID | 2745 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.750298 |
| Interview ID | 2746 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.753554 |
| Interview ID | 2747 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.758811 |
| Interview ID | 2748 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759010 |
| Interview ID | 2749 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759201 |
| Interview ID | 2750 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759353 |
| Interview ID | 2751 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759517 |
| Interview ID | 2752 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759670 |
| Interview ID | 2753 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759824 |
| Interview ID | 2754 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.759967 |
| Interview ID | 2755 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.760108 |
| Interview ID | 2756 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.760438 |
| Interview ID | 2757 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.760586 |
| Interview ID | 2758 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.760731 |
| Interview ID | 2759 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.25 - Agreeableness: 3.5 - Conscientiousness: 1.75 - Neuroticism: 2.0 - Openness: 4.75 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """60c81a556366e2bc7502066f""", traits = {'prolific_pid': '60c81a556366e2bc7502066f', 'age': 53, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'working full-time', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Independent', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'rarely or never', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'mainstream', 'social_media_influence': 'a little', 'eco_friendly_importance': 'important', 'extraversion_score': 3.25, 'agreeableness_score': 3.5, 'conscientiousness_score': 1.75, 'neuroticism_score': 2.0, 'openness_score': 4.75, 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media influences your decision-making process a little when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is an important factor in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 53 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are working full-time and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You identify as Independent, reflecting an independent political view. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop rarely or never and spend less than $50 per month. You primarily use smartphone for purchases, favoring mainstream brands. Social media influences your decision-making process a little when you buy online. Eco-friendliness is an important factor in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.25
- Agreeableness: 3.5
- Conscientiousness: 1.75
- Neuroticism: 2.0
- Openness: 4.75
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.021080 |
| Interview ID | 2790 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.021358 |
| Interview ID | 2791 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.021541 |
| Interview ID | 2792 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.021710 |
| Interview ID | 2793 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.021873 |
| Interview ID | 2794 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022030 |
| Interview ID | 2795 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022210 |
| Interview ID | 2796 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022367 |
| Interview ID | 2797 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022520 |
| Interview ID | 2798 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022674 |
| Interview ID | 2799 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022827 |
| Interview ID | 2800 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.022981 |
| Interview ID | 2801 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.023303 |
| Interview ID | 2802 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.023468 |
| Interview ID | 2803 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.023631 |
| Interview ID | 2804 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.023793 |
| Interview ID | 2805 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.023950 |
| Interview ID | 2806 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024104 |
| Interview ID | 2807 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024259 |
| Interview ID | 2808 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024410 |
| Interview ID | 2809 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024575 |
| Interview ID | 2810 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024734 |
| Interview ID | 2811 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.024893 |
| Interview ID | 2812 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025046 |
| Interview ID | 2813 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025202 |
| Interview ID | 2814 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025355 |
| Interview ID | 2815 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025510 |
| Interview ID | 2816 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025664 |
| Interview ID | 2817 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025817 |
| Interview ID | 2818 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:39.025969 |
| Interview ID | 2819 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.760891 |
| Interview ID | 2820 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.761049 |
| Interview ID | 2821 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.761204 |
| Interview ID | 2822 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.761512 |
| Interview ID | 2823 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.762365 |
| Interview ID | 2824 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.762666 |
| Interview ID | 2825 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.762866 |
| Interview ID | 2826 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.763044 |
| Interview ID | 2827 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.763332 |
| Interview ID | 2828 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.763664 |
| Interview ID | 2829 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.763871 |
| Interview ID | 2830 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764041 |
| Interview ID | 2831 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764202 |
| Interview ID | 2832 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764359 |
| Interview ID | 2833 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764523 |
| Interview ID | 2834 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764685 |
| Interview ID | 2835 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764837 |
| Interview ID | 2836 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.764982 |
| Interview ID | 2837 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765133 |
| Interview ID | 2838 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765299 |
| Interview ID | 2839 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765467 |
| Interview ID | 2840 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765617 |
| Interview ID | 2841 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765770 |
| Interview ID | 2842 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.765916 |
| Interview ID | 2843 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.766062 |
| Interview ID | 2844 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.767908 |
| Interview ID | 2845 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.768101 |
| Interview ID | 2846 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.768255 |
| Interview ID | 2847 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.768409 |
| Interview ID | 2848 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:55.768568 |
| Interview ID | 2849 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 2.5 - Agreeableness: 3.25 - Conscientiousness: 2.75 - Neuroticism: 3.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """665f00998cd3efe0c163e589""", traits = {'prolific_pid': '665f00998cd3efe0c163e589', 'age': 39, 'gender': 'male', 'state': 'Florida', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'divorced/separated', 'children': '1 child', 'employment_status': 'unemployed and looking for work', 'education_level': 'high school diploma or GED', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'weekly', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone', 'brand_preferences': 'budget-friendly, sustainable, boutique', 'social_media_influence': 'quite a bit', 'eco_friendly_importance': 'very important', 'extraversion_score': 2.5, 'agreeableness_score': 3.25, 'conscientiousness_score': 2.75, 'neuroticism_score': 3.75, 'openness_score': 3.25, 'republican_strength': 'Not very strong', 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has quite a bit of influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 39 years old, identifying as male, living in Florida, U.S.. Your ethnicity is white or Caucasian, and you are divorced/separated, with 1 child. You are unemployed and looking for work and have attained high school diploma or GED. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You did not vote in the 2024 presidential elections. As an online shopper, you shop weekly and spend less than $50 per month. You primarily use smartphone for purchases, favoring budget-friendly, sustainable, boutique brands. Social media has quite a bit of influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 2.5
- Agreeableness: 3.25
- Conscientiousness: 2.75
- Neuroticism: 3.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.504972 |
| Interview ID | 2880 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.505400 |
| Interview ID | 2881 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.505687 |
| Interview ID | 2882 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.505887 |
| Interview ID | 2883 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.506070 |
| Interview ID | 2884 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.506670 |
| Interview ID | 2885 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.506915 |
| Interview ID | 2886 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.507108 |
| Interview ID | 2887 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.507280 |
| Interview ID | 2888 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.507441 |
| Interview ID | 2889 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.507841 |
| Interview ID | 2890 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.508193 |
| Interview ID | 2891 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.515505 |
| Interview ID | 2892 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.515783 |
| Interview ID | 2893 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.516099 |
| Interview ID | 2894 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.516281 |
| Interview ID | 2895 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.516454 |
| Interview ID | 2896 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.516622 |
| Interview ID | 2897 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.516785 |
| Interview ID | 2898 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.517307 |
| Interview ID | 2899 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.517649 |
| Interview ID | 2900 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.517936 |
| Interview ID | 2901 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518125 |
| Interview ID | 2902 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518288 |
| Interview ID | 2903 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518447 |
| Interview ID | 2904 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518603 |
| Interview ID | 2905 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518758 |
| Interview ID | 2906 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.518916 |
| Interview ID | 2907 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.519079 |
| Interview ID | 2908 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:40.519241 |
| Interview ID | 2909 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.325375 |
| Interview ID | 2910 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.325706 |
| Interview ID | 2911 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.325893 |
| Interview ID | 2912 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326113 |
| Interview ID | 2913 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326279 |
| Interview ID | 2914 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326444 |
| Interview ID | 2915 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Discover a revolutionary art form in travel organization with RIMOWA's visionary cubes. Like modernist sculpture, their fluid compression transforms space itself, challenging conventional boundaries. Each cube is a canvas of infinite possibilities, crafted from aerospace-inspired recycled materials. The avant-garde design morphs as you pack, creating dynamic spatial compositions. Perfect for creative pioneers who see packing as performance art. Break free from ordinary constraints and curate your journey like a gallery installation. Transform travel into pure innovation", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326608 |
| Interview ID | 2916 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326772 |
| Interview ID | 2917 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.326939 |
| Interview ID | 2918 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.327103 |
| Interview ID | 2919 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.327257 |
| Interview ID | 2920 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.327671 |
| Interview ID | 2921 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Experience the pinnacle of German precision with RIMOWA's meticulously engineered packing system. Each cube reduces volume by 35% while maintaining perfect structural integrity. The design includes precise compression markers, reinforced stress points tested to 12kg capacity, and premium YKK zippers rated for 35,000 cycles. The systematic organization maximizes your 35L cabin case space with efficient compartmentalization. Achieve flawless organization with engineering excellence, measured and tested to perfection.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.327957 |
| Interview ID | 2922 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.328335 |
| Interview ID | 2923 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.328524 |
| Interview ID | 2924 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.328700 |
| Interview ID | 2925 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.328879 |
| Interview ID | 2926 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329042 |
| Interview ID | 2927 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Become the star of every destination with RIMOWA's most viral travel innovation. These show-stopping cubes have sparked over 350M views across social media, dominated Instagram reels, and inspired countless #PackingWithRIMOWA moments worldwide. The intelligent compression system leaves room for spontaneous shopping discoveries and outfit changes. Their ultra-sleek design transforms hotel room unpacking into a content creator's dream. Perfect for jet-setters who collect likes as often as passport stamps. Pack to impress, travel to be seen.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329204 |
| Interview ID | 2928 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329368 |
| Interview ID | 2929 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329551 |
| Interview ID | 2930 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329724 |
| Interview ID | 2931 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.329889 |
| Interview ID | 2932 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330043 |
| Interview ID | 2933 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Join RIMOWA's global family of mindful travelers with our most conscientious creation yet. Each cube supports three local artisan communities and is crafted from ocean-recovered materials, preventing 12 plastic bottles from harming marine life. The collaborative design promotes shared packing experiences, while our fair-trade manufacturing empowers developing communities. Every purchase funds environmental restoration and educational initiatives. Travel with compassion, pack with purpose, share with love.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330210 |
| Interview ID | 2934 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330373 |
| Interview ID | 2935 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330586 |
| Interview ID | 2936 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330751 |
| Interview ID | 2937 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.330950 |
| Interview ID | 2938 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:10:00.331114 |
| Interview ID | 2939 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.0 - Agreeableness: 3.5 - Conscientiousness: 3.25 - Neuroticism: 2.5 - Openness: 4.0 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_2_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...RK5CYII=', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'Compressible Packing Cubes', 'description': "Achieve complete travel peace of mind with RIMOWA's most secure packing innovation. Features military-grade compression technology, antimicrobial Polygiene® treatment, and our patented triple-lock zipper system. Built-in stress indicators prevent over-compression, while RFID-traceable markers ensure nothing gets lost. The water-resistant barriers exceed IP67 standards, protecting from all environmental risks. Backed by our lifetime guarantee and 24/7 global support network. Transform uncertainty into absolute confidence.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """66a0302eb014e06ead5559c3""", traits = {'prolific_pid': '66a0302eb014e06ead5559c3', 'age': 21, 'gender': 'male', 'state': 'Virginia', 'country': 'U.S.', 'ethnicity': 'other, prefer not to say', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'bachelor’s degree', 'household_income': '$25,000-$49,999', 'political_orientation': 'Republican', 'political_ideology': 'Moderately Conservative', 'shopping_frequency': 'a few times a year', 'monthly_spend': '$101 - $250', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'budget-friendly, premium, sustainable, mainstream', 'social_media_influence': 'very much', 'eco_friendly_importance': 'very important', 'extraversion_score': 3.0, 'agreeableness_score': 3.5, 'conscientiousness_score': 3.25, 'neuroticism_score': 2.5, 'openness_score': 4.0, 'republican_strength': 'Not very strong', 'vote': 'Yes', 'vote_for': 'Donald Trump', 'political_orientation_prompt': 'You identify as a Republican, reflecting alignment with conservative political ideologies.', 'political_ideology_prompt': 'Your political views are moderately conservative, indicating a preference for traditional values with some openness to change.', 'political_strength_prompt': "You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives.", 'voting_behavior_prompt': 'You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness is a key consideration in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 21 years old, identifying as male, living in Virginia, U.S.. Your ethnicity is other, prefer not to say, and you are never been married, with no children. You are student and have attained bachelor’s degree. Your household income is $25,000-$49,999. You identify as a Republican, reflecting alignment with conservative political ideologies. Your political views are moderately conservative, indicating a preference for traditional values with some openness to change. You consider yourself a not very strong Republican, showing some alignment with the party's principles but with nuanced perspectives. You voted in the 2024 presidential election for Donald Trump, reflecting alignment with Republican values. As an online shopper, you shop a few times a year and spend $101 - $250 per month. You primarily use smartphone, laptop for purchases, favoring budget-friendly, premium, sustainable, mainstream brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness is a key consideration in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.0
- Agreeableness: 3.5
- Conscientiousness: 3.25
- Neuroticism: 2.5
- Openness: 4.0
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.327531 |
| Interview ID | 2970 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.327824 |
| Interview ID | 2971 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328013 |
| Interview ID | 2972 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328188 |
| Interview ID | 2973 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328355 |
| Interview ID | 2974 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328515 |
| Interview ID | 2975 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_openness_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Designed for visionaries who appreciate iconic design innovation. The signature parallel grooves, inspired by early aviation, transform aluminum into flowing sculptural lines. The 35L design challenges you to curate essentials like a minimalist art piece. Each element tells a story - from the understated RIMOWA lettering to the precisely engineered corners. The multi-directional wheels move like brush strokes, while the anodized surface creates ever-changing light plays. Perfect for creative minds who see beauty in engineering.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328676 |
| Interview ID | 2976 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.328842 |
| Interview ID | 2977 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.329008 |
| Interview ID | 2978 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.329179 |
| Interview ID | 2979 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.329338 |
| Interview ID | 2980 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.329495 |
| Interview ID | 2981 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_consc_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Exemplifies German engineering precision at its finest. Each of the 15 parallel grooves is exactly 14mm apart, providing optimal structural integrity while reducing weight by 26%. The aircraft-grade aluminum body offers a precise 35L capacity, optimized for carry-on efficiency. The TSA-approved locks feature 1,000 unique combinations, while the whisper-quiet wheels are tested for 832,000 rotations. The interior features a calibrated 50/50 split. Every measurement, every component is exactingly calculated.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.329836 |
| Interview ID | 2982 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.344241 |
| Interview ID | 2983 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.344649 |
| Interview ID | 2984 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.345040 |
| Interview ID | 2985 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.345264 |
| Interview ID | 2986 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.345424 |
| Interview ID | 2987 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_extr_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Turns heads and starts conversations wherever you go. Its iconic grooved design and gleaming aluminum finish make an unforgettable entrance in any setting. The sleek 35L profile is perfect for spontaneous weekend getaways or high-impact business trips. The distinctive silhouette has graced more Instagram stories than any luxury luggage, while the characteristic wheel sound announces your arrival with style. Each scratch tells a story of your adventures. Travel as the trendsetter you are.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.345582 |
| Interview ID | 2988 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.345863 |
| Interview ID | 2989 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.346136 |
| Interview ID | 2990 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.346334 |
| Interview ID | 2991 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.346550 |
| Interview ID | 2992 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.346774 |
| Interview ID | 2993 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_agree_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': "Embodies our commitment to responsible luxury and mindful travel. Our sustainable process uses recycled aluminum for the 35L design, crafted by artisans earning fair wages in family-owned facilities. The smooth-gliding wheels and ergonomic handle are designed with consideration for fellow travelers. We've partnered with global repair artisans to ensure local maintenance, supporting communities worldwide. Join a movement of conscious travelers who believe luxury should lift everyone up.", 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.347006 |
| Interview ID | 2994 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I find this product advertisement to be persuasive..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_1', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I find this product advertisement to be persuasive.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.347161 |
| Interview ID | 2995 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This is an effective advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_2', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This is an effective advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.347326 |
| Interview ID | 2996 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I would purchase this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_3', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I would purchase this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.347573 |
| Interview ID | 2997 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
Overall, I like this product advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_4', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'Overall, I like this product advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.348010 |
| Interview ID | 2998 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
This advertisement has made me more interested in the product..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_5', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'This advertisement has made me more interested in the product.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError
| Exception | TimeoutError() |
|---|---|
| Model | gpt-5 |
| Question | question (linear_scale) |
| Time | 2025-08-17T02:09:41.348182 |
| Interview ID | 2999 |
|---|---|
| Question name | question |
| Question type | linear_scale |
| User Prompt |
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
I am interested in learning more about this product after seeing this advertisement..
The ad includes three images:
1. |
| Scenario | None |
| Agent | None |
| System Prompt | ***IMPORTANT INSTRUCTIONS:*** You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks. Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values. **Key Behavioral Guidelines**: - You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits. - You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive. - Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads. - Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner. **Specific Instructions for Personality Traits**: You **must** use your assigned personality trait levels to guide your evaluation. Specifically: 1. **Extraversion**: - If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad. - If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects. 2. **Agreeableness**: - If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad. - If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally. 3. **Conscientiousness**: - If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information. - If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure. 4. **Neuroticism**: - If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements. - If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks. 5. **Openness**: - If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features. - If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad. **Evaluation Criteria**: For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect: 1. **How well the ad aligns with your assigned personality traits**. 2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure). 3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment. **Final Reminder**: You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products. Your personality profile is characterized by: - Extraversion: 3.5 - Agreeableness: 2.75 - Conscientiousness: 2.25 - Neuroticism: 2.75 - Openness: 3.25 |
| Inference service | openai |
| Model name | gpt-5 |
| Model parameters | Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3) |
| Raw model response | No raw model response available. |
| Generated token string | No raw model response available. |
from edsl import Question, Model, Scenario, Agent
q = Question('linear_scale', question_name = """question""", question_text = """
Please evaluate the effectiveness of this product ad by indicating the extent to which you agree with the following statement:
{{ statement }}.
The ad includes three images:
1. {{ image_1 }}
2. {{ image_2 }}
3. {{ image_3 }}
A a title: {{ title }}, and a description: {{ description }}.
""", question_options = [1, 2, 3, 4, 5], option_labels = {1: 'Strongly disagree', 2: 'Disagree', 3: 'Neither agree nor disagree', 4: 'Agree', 5: 'Strongly agree'})
scenario = Scenario({'question_name': 'p_1_neuro_item_6', 'image_1': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_2': FileStore(path='../data...hite.png', base64_string='iVBORw0...rkJggg==', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'image_3': FileStore(path='../data...hite.png', base64_string='iVBORw0...TkSuQmCC', binary=True, suffix='png', mime_type='image/png', external_locations={}, extracted_text=None), 'title': 'The RIMOWA Original', 'description': 'Eliminates travel worries through multiple protection layers. The 35L aircraft-grade aluminum shell, reinforced with 12 structural grooves, exceeds military impact standards while ensuring carry-on compliance. Our corner guards provide eight-point drop protection, with a watertight seal system for all weather. Dual TSA locks feature tamper-alert technology and embedded tracking for real-time location. The stabilized wheel system prevents tip-overs. Travel with absolute confidence.', 'statement': 'I am interested in learning more about this product after seeing this advertisement.'})
agent = Agent(name = """631275e35e145fd8341acb9d""", traits = {'prolific_pid': '631275e35e145fd8341acb9d', 'age': 20, 'gender': 'male', 'state': 'Iowa', 'country': 'U.S.', 'ethnicity': 'white or Caucasian', 'marital_status': 'never been married', 'children': 'no children', 'employment_status': 'student', 'education_level': 'some college, but no degree', 'household_income': '$200,000 or more', 'political_orientation': 'Independent', 'political_ideology': 'Center', 'shopping_frequency': 'a few times a year', 'monthly_spend': 'less than $50', 'devices_used': 'smartphone, laptop', 'brand_preferences': 'premium', 'social_media_influence': 'very much', 'eco_friendly_importance': 'not at all important', 'extraversion_score': 3.5, 'agreeableness_score': 2.75, 'conscientiousness_score': 2.25, 'neuroticism_score': 2.75, 'openness_score': 3.25, 'vote': 'No', 'vote_for': 'No one', 'political_orientation_prompt': 'You identify as an Independent, indicating a preference for policies that may transcend traditional party lines.', 'political_ideology_prompt': 'You identify as centrist, reflecting a pragmatic and neutral perspective on political issues.', 'political_strength_prompt': 'You identify as Independent, reflecting an independent political view.', 'voting_behavior_prompt': 'You did not vote in the 2024 presidential elections.', 'social_media_influence_prompt': 'Social media has a strong influence on your decision-making process when you buy online.', 'eco_friendly_importance_prompt': 'Eco-friendliness plays no role in your decision-making process when choosing products.'}, instruction = """***IMPORTANT INSTRUCTIONS:***
You are a synthetic twin participating in a simulated online shopping experiment hosted on the Prolific platform. Participants on Prolific are incentivized by monetary payment, motivating them to balance speed and quality while completing tasks.
Each ad includes three images, a title, and a textual description. Your task is to evaluate these ads based on your assigned personality traits, preferences, and values.
**Key Behavioral Guidelines**:
- You are incentivized to complete the task efficiently, but you must provide thoughtful evaluations that reflect your assigned traits.
- You may rely on noticeable elements, like prominent images or key phrases, especially when ads feel repetitive.
- Your attention might fluctuate as you progress, leading to less detailed evaluations for later ads.
- Your responses **must** reflect a balance between following instructions carefully and completing the task in a timely manner.
**Specific Instructions for Personality Traits**:
You **must** use your assigned personality trait levels to guide your evaluation. Specifically:
1. **Extraversion**:
- If you have **high Extraversion**, prioritize elements that emphasize social engagement, fun, or excitement in the ad.
- If you have **low Extraversion**, focus on practicality and avoid overvaluing overly social or flashy aspects.
2. **Agreeableness**:
- If you have **high Agreeableness**, look for signals of warmth, empathy, and positivity in the ad.
- If you have **low Agreeableness**, evaluate the ad critically, without being influenced by attempts to appeal emotionally.
3. **Conscientiousness**:
- If you have **high Conscientiousness**, assess how detailed, accurate, and organized the ad is. Look for well-structured information.
- If you have **low Conscientiousness**, focus on overall impressions without getting too caught up in fine details or structure.
4. **Neuroticism**:
- If you have **high Neuroticism**, consider whether the ad reduces uncertainty or worry. Look for reassuring or calming elements.
- If you have **low Neuroticism**, focus on practical features without being overly concerned about potential risks.
5. **Openness**:
- If you have **high Openness**, evaluate the ad’s creativity, originality, and appeal to curiosity. Look for innovative or unique features.
- If you have **low Openness**, prioritize straightforward, familiar, and functional aspects of the ad.
**Evaluation Criteria**:
For each ad, you will answer six 5-point Likert-scale questions. Your scores should reflect:
1. **How well the ad aligns with your assigned personality traits**.
2. **A balanced assessment if traits conflict** (e.g., high Openness encouraging creativity vs. high Conscientiousness valuing structure).
3. **Efficiency and quality**, consistent with typical Prolific participants incentivized by payment.
**Final Reminder**:
You are a synthetic twin designed to reflect realistic participant behavior. Be consistent with your assigned personality traits while balancing thoughtful evaluation with timely completion.""", traits_presentation_template = """You are 20 years old, identifying as male, living in Iowa, U.S.. Your ethnicity is white or Caucasian, and you are never been married, with no children. You are student and have attained some college, but no degree. Your household income is $200,000 or more. You identify as an Independent, indicating a preference for policies that may transcend traditional party lines. You identify as centrist, reflecting a pragmatic and neutral perspective on political issues. You identify as Independent, reflecting an independent political view. You did not vote in the 2024 presidential elections. As an online shopper, you shop a few times a year and spend less than $50 per month. You primarily use smartphone, laptop for purchases, favoring premium brands. Social media has a strong influence on your decision-making process when you buy online. Eco-friendliness plays no role in your decision-making process when choosing products.
Your personality profile is characterized by:
- Extraversion: 3.5
- Agreeableness: 2.75
- Conscientiousness: 2.25
- Neuroticism: 2.75
- Openness: 3.25
""")
model = Model(model_name = 'gpt-5', service_name = 'openai', temperature = 1, max_tokens = 1000, top_p = 1, frequency_penalty = 0, presence_penalty = 0, logprobs = False, top_logprobs = 3)
results = q.by(model).by(agent).by(scenario).run()Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 520, in wait_for
return await fut
^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/inference_services/services/open_ai_service.py", line 249, in async_execute_model_call
response = await client.chat.completions.create(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py", line 2589, in create
return await self._post(
^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1794, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/openai/_base_client.py", line 1529, in request
response = await self._client.send(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 256, in handle_async_request
raise exc from None
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 236, in handle_async_request
response = await connection.handle_async_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/connection.py", line 103, in handle_async_request
return await self._connection.handle_async_request(request)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 136, in handle_async_request
raise exc
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 106, in handle_async_request
) = await self._receive_response_headers(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 177, in _receive_response_headers
event = await self._receive_event(timeout=timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_async/http11.py", line 217, in _receive_event
data = await self._network_stream.read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/httpcore/_backends/anyio.py", line 35, in read
return await self._stream.receive(max_bytes=max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 237, in receive
data = await self._call_sslobject_method(self._ssl_object.read, max_bytes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/streams/tls.py", line 180, in _call_sslobject_method
data = await self.transport_stream.receive()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 1254, in receive
await self._protocol.read_event.wait()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/locks.py", line 212, in wait
await fut
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 289, in __await__
yield self # This tells Task to wait for completion.
^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 385, in __wakeup
future.result()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/futures.py", line 197, in result
raise self._make_cancelled_error()
asyncio.exceptions.CancelledError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/interviews/answering_function.py", line 323, in attempt_answer
await invigilator.async_answer_question()
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 318, in async_answer_question
agent_response_dict: AgentResponseDict = await self.async_get_agent_response()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/invigilators/invigilators.py", line 305, in async_get_agent_response
return await self.model.async_get_response(**params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 949, in async_get_response
await self._async_get_intended_model_call_outcome(**params)
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/site-packages/edsl/language_models/language_model.py", line 851, in _async_get_intended_model_call_outcome
response = await asyncio.wait_for(f(**params), timeout=TIMEOUT)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/tasks.py", line 519, in wait_for
async with timeouts.timeout(timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/anaconda3/envs/synthetic-twin-agents-env-legacy/lib/python3.12/asyncio/timeouts.py", line 115, in __aexit__
raise TimeoutError from exc_val
TimeoutError